Your rig

CPU only · DDR4 dual-channel · 32 GB

DDR4-3200 · 51 GB/s · 25.6 GB usable of 32 GB system RAM
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Context length

KV cache at f16, 128K tokens

Quality floor
Q8_0 — near-lossless Q6_K Q5_K_M Q4_K_M — recommended Q3_K_M Q2_K — damaged
KV cache type
Runtime
Ollamallama.cppLM Studio

3 of 5 runtimes drive this device.

Allow CPU offload Include partial-offload fits

Offloaded layers run at 60 GB/s host bandwidth — expect single-digit tokens per second.

Which one should I actually run?

Best models for your CPU only · DDR4 dual-channel

Updated 21 Aug 2026 5 new this week, 14 this month

What do you want to do? Each row is the best-ranked model on that use case's shortlist that fits at Q2_K and 128K. The ordering is editorial; the sizes and speeds are computed. How the shortlists work.

RecommendationModelWhyQuant · totalTok/s est.
Best overall Qwen3.8 27B New this week
Alibaba · Apache 2.0
Best capability per gigabyte: a current-generation dense 27B with vision and 262K context. Q2_K · 19.4 GB 2.0 Runs great
Best for coding Qwen3.8 27B New this week
Alibaba · Apache 2.0
Terminal-Bench 73, DeepSWE 42 — a generation ahead of anything else that fits 24 GB. Q2_K · 19.4 GB 2.0 Runs great
Best reasoning Qwen3.8 27B New this week
Alibaba · Apache 2.0
Thinking mode plus the best agentic reasoning at 24 GB. Q2_K · 19.4 GB 2.0 Runs great
Best for writing Gemma 4 26B-A4B
Google · Apache 2.0
Gemma 4 prose at MoE speed, with room for a long draft in context. Q2_K · 16.1 GB 6.4 Runs great
Best vision Qwen3.8 27B New this week
Alibaba · Apache 2.0
Image and video in, OSWorld 84 — the strongest local vision-language model at 24 GB. Q2_K · 19.4 GB 2.0 Runs great
Best for agents Qwen3.8 27B New this week
Alibaba · Apache 2.0
Computer use and tool calling are what 3.8 was trained for (OSWorld 84). Q2_K · 19.4 GB 2.0 Runs great
Best translation Qwen3.8 27B New this week
Alibaba · Apache 2.0
119 languages, and Qwen translations read as idiomatic rather than literal. Q2_K · 19.4 GB 2.0 Runs great
Fastest good model Qwen3.6 35B-A3B
Alibaba · Apache 2.0
3.3B active per token: the fastest model that still competes with dense 27Bs. Q2_K · 17.1 GB 7.4 Runs great
Best long context Qwen3.8 27B New this week
Alibaba · Apache 2.0
262K native, and only 16 of 64 blocks keep a KV cache — long context is cheap here. Q2_K · 19.4 GB
at 128K context
2.0 Runs great

Everything that fits

Runs great

41 of 76 · fits with headroom for a longer prompt
ModelParamsQuantWeights +KV 128KTotal VRAM headroom Tok/sRuntime
Qwen3.6 35B-A3B 35.9B MoE / 3.3B act Q2_K 14.0 GB 2.50 GB 17.1 GB
8.5 GB free
7.4 llama.cpp Run
Ornith 1.5 35B-A3B New this week 35.9B MoE / 3.3B act Q2_K 14.0 GB 2.50 GB 17.1 GB
8.5 GB free
7.4 llama.cpp Run
Olmo 3.1 32B Instruct 32.2B Q2_K 12.6 GB 4.75 GB 17.9 GB
7.7 GB free
1.7 llama.cpp Run
Nemotron 3.5 Lightning 30B-A3B New 31.6B MoE / 3.2B act Q2_K 12.3 GB 0.75 GB 13.7 GB
11.9 GB free
7.6 llama.cpp Run
GLM-4.7-Flash 30B-A3B 31.2B MoE / 3B act Q2_K 12.2 GB 6.61 GB 19.4 GB
6.2 GB free
8.1 llama.cpp Run
Muse Glimmer 30B New 29.8B Q2_K 11.6 GB 1.70 GB 13.9 GB
11.7 GB free
1.8 llama.cpp Run
Qwen3.8 27B New this week 27.8B Q2_K 10.8 GB 8.00 GB 19.4 GB
6.2 GB free
2.0 llama.cpp Run
Qwen3.6 27B 27.8B Q2_K 10.8 GB 8.00 GB 19.4 GB
6.2 GB free
2.0 llama.cpp Run
Gemma 3 27B 27.4B Q2_K 10.7 GB 10.41 GB 21.7 GB
3.9 GB free
2.0 llama.cpp Run
Gemma 4 26B-A4B 26.5B MoE / 3.8B act Q2_K 10.3 GB 5.20 GB 16.1 GB
9.5 GB free
6.4 llama.cpp Run
gpt-oss 20B 20.9B MoE / 3.6B act MXFP4 10.8 GB 3.00 GB 14.4 GB
11.2 GB free
5.1 llama.cpp Run
Phi-4 14B 14.7B Q2_K 5.7 GB 3.13 GB 9.5 GB
16.1 GB free
3.7 llama.cpp Run
Gemma 3 12B 12.2B Q2_K 4.8 GB 8.31 GB 13.7 GB
11.9 GB free
4.5 llama.cpp Run
Gemma 4 12B 12B Q2_K 4.7 GB 8.31 GB 13.6 GB
12.0 GB free
4.6 llama.cpp Run
Qwen3.5 9B 9.65B Q2_K 3.8 GB 4.00 GB 8.4 GB
17.2 GB free
5.7 llama.cpp Run
Ornith 1.5 9B New this week 9.41B Q2_K 3.7 GB 4.00 GB 8.3 GB
17.3 GB free
5.8 llama.cpp Run
Ministral 3 8B 8.92B Q2_K 3.5 GB 17.00 GB 21.1 GB
4.5 GB free
6.1 llama.cpp Run
LFM2.5 8B-A1B 8.47B MoE / 1.5B act Q2_K 3.3 GB 1.46 GB 5.4 GB
20.2 GB free
16 llama.cpp Run
Fara 7B 8.29B Q2_K 3.2 GB 6.84 GB 10.7 GB
14.9 GB free
6.6 llama.cpp Run
Llama 3.1 8B Instruct 8.03B Q2_K 3.1 GB 16.00 GB 19.7 GB
5.9 GB free
6.8 llama.cpp Run
Gemma 4 E4B 8.0B Q2_K 3.1 GB 1.78 GB 5.5 GB
20.1 GB free
6.9 llama.cpp Run
Ling 3.0 Tiny 7.9B-A1.3B New 7.9B MoE / 1.3B act Q2_K 3.1 GB 0.84 GB 4.5 GB
21.1 GB free
19 llama.cpp Run
DeepSeek-R1-Distill-Qwen 7B 7.62B Q2_K 3.0 GB 7.00 GB 10.6 GB
15.0 GB free
7.2 llama.cpp Run
Qwen2.5-Coder 7B 7.62B Q2_K 3.0 GB 7.00 GB 10.6 GB
15.0 GB free
7.2 llama.cpp Run
Olmo 3 7B Instruct 7.3B Q2_K 2.8 GB 9.50 GB 12.9 GB
12.7 GB free
7.5 llama.cpp Run
Mistral 7B Instruct v0.3 7.25B Q2_K 2.8 GB 4.00 GB 7.4 GB
18.2 GB free
7.6 llama.cpp Run
Gemma 4 E2B 5.1B Q2_K 2.0 GB 0.89 GB 3.5 GB
22.1 GB free
11 llama.cpp Run
Qwen3.5 4B 4.66B Q2_K 1.8 GB 4.00 GB 6.4 GB
19.2 GB free
12 llama.cpp Run
Gemma 3 4B 4.3B Q2_K 1.7 GB 3.11 GB 5.4 GB
20.2 GB free
13 llama.cpp Run
Qwen3 4B 4.02B Q2_K 1.6 GB 4.50 GB 6.7 GB
18.9 GB free
14 llama.cpp Run
Ministral 3 3B 3.85B Q2_K 1.5 GB 13.00 GB 15.1 GB
10.5 GB free
14 llama.cpp Run
Phi-4-mini 3.8B 3.84B Q2_K 1.5 GB 16.00 GB 18.1 GB
7.5 GB free
14 llama.cpp Run
Granite 4.1 3B 3.4B Q2_K 1.3 GB 10.00 GB 11.9 GB
13.7 GB free
16 llama.cpp Run
Llama 3.2 3B Instruct 3.21B Q2_K 1.3 GB 14.00 GB 15.9 GB
9.7 GB free
17 llama.cpp Run
LFM2.5 2.6B New 2.7B Q2_K 1.1 GB 2.00 GB 3.7 GB
21.9 GB free
20 llama.cpp Run
Qwen3.5 2B 2.27B Q2_K 0.9 GB 1.50 GB 3.0 GB
22.6 GB free
24 llama.cpp Run
Qwen3 1.7B 1.72B Q2_K 0.7 GB 3.50 GB 4.8 GB
20.8 GB free
32 llama.cpp Run
Llama 3.2 1B Instruct 1.24B Q2_K 0.5 GB 4.00 GB 5.1 GB
20.5 GB free
44 llama.cpp Run
Gemma 3 1B 1.0B Q2_K 0.4 GB 0.14 GB 1.1 GB
24.5 GB free
55 llama.cpp Run
Qwen3.5 0.8B 0.87B Q2_K 0.3 GB 1.50 GB 2.4 GB
23.2 GB free
63 llama.cpp Run
Qwen3 0.6B 0.6B Q2_K 0.2 GB 3.50 GB 4.3 GB
21.3 GB free
91 llama.cpp Run

Runs — tight

5 models · fits at 128K, drop context or quant to go longer
ModelParamsQuantWeights +KV 128KTotal VRAM headroom Tok/sRuntime
Qwen3 30B-A3B 30.5B MoE / 3.3B act Q2_K 11.9 GB 12.00 GB 24.5 GB
1.1 GB free
7.4 llama.cpp Run
Qwen3 Coder 30B-A3B 30.5B MoE / 3.3B act Q2_K 11.9 GB 12.00 GB 24.5 GB
1.1 GB free
7.4 llama.cpp Run
Mistral NeMo 12B 12.2B Q2_K 4.8 GB 20.00 GB 25.4 GB
0.2 GB free
4.5 llama.cpp Run
Granite 4.1 8B 8.79B Q2_K 3.4 GB 20.00 GB 24.0 GB
1.6 GB free
6.2 llama.cpp Run
Qwen3 8B 8.19B Q2_K 3.2 GB 18.00 GB 21.8 GB
3.8 GB free
6.7 llama.cpp Run

Won't fit in VRAM

30 models · some are possible with CPU offload
ModelParamsQuantWeights +KV 128KTotal Over budget Tok/sRuntime
Kimi K3 2.8T-A104B New 2780B MoE / 104B act Q2_K 1084.2 GB 3.38 GB 1088.2 GB +1062.6 GB ~0.2 llama.cpp Why
Qwen3.8 2.4T-A95B New 2446B MoE / 95B act Q2_K 953.9 GB 11.50 GB 966.0 GB +940.4 GB ~0.3 llama.cpp Why
DeepSeek V4 Pro 1.6T-A49B New 1650B MoE / 49B act Q2_K 643.5 GB 8.58 GB 652.7 GB +627.1 GB ~0.5 llama.cpp Why
Kimi K2.6 1T-A32B 1027B MoE / 32B act Q2_K 400.5 GB 8.58 GB 409.7 GB +384.1 GB ~0.8 llama.cpp Why
GLM-5.2 744B-A40B 753B MoE / 40B act Q2_K 293.7 GB 10.97 GB 305.2 GB +279.6 GB ~0.6 llama.cpp Why
DeepSeek-R1 671B 671B MoE / 37B act Q2_K 261.7 GB 8.58 GB 270.9 GB +245.3 GB ~0.7 llama.cpp Why
Qwen3.5 397B-A17B 403B MoE / 17B act Q2_K 157.2 GB 3.75 GB 161.5 GB +135.9 GB ~1.4 llama.cpp Why
Ornith 1.5 397B-A17B New this week 397B MoE / 17B act Q2_K 154.8 GB 3.75 GB 159.2 GB +133.6 GB ~1.4 llama.cpp Why
DeepSeek V4 Flash 284B-A13B New 284B MoE / 13B act Q2_K 110.8 GB 6.05 GB 117.4 GB +91.8 GB ~1.9 llama.cpp Why
Qwen3 235B-A22B 235B MoE / 22B act Q2_K 91.6 GB 23.50 GB 115.7 GB +90.1 GB ~1.1 llama.cpp Why
Qwen3.5 122B-A10B 125B MoE / 10B act Q2_K 48.7 GB 3.00 GB 52.3 GB +26.7 GB ~2.4 llama.cpp Why
Nemotron 3 Super 120B-A12B 124B MoE / 12B act Q2_K 48.4 GB 1.00 GB 50.0 GB +24.4 GB ~2.0 llama.cpp Why
Ling 3.0 Flash 124B-A5B New 124B MoE / 5.1B act Q2_K 48.4 GB 0.98 GB 49.9 GB +24.3 GB ~4.8 llama.cpp Why
Mistral Small 4 119B-A6B 119B MoE / 6.5B act Q2_K 46.4 GB 2.81 GB 49.8 GB +24.2 GB ~3.7 llama.cpp Why
gpt-oss 120B 117B MoE / 5.1B act MXFP4 60.5 GB 4.50 GB 65.6 GB +40.0 GB ~3.6 llama.cpp Why
Llama 4 Scout 109B-A17B 109B MoE / 17B act Q2_K 42.5 GB 7.13 GB 50.2 GB +24.6 GB ~1.4 llama.cpp Why
Llama 3.3 70B Instruct 70.6B Q2_K 27.5 GB 40.00 GB 68.1 GB +42.5 GB ~0.8 llama.cpp Why
DeepSeek-R1-Distill-Llama 70B 70.6B Q2_K 27.5 GB 40.00 GB 68.1 GB +42.5 GB ~0.8 llama.cpp Why
LLM-jp 4 33B Thinking New this week 33.2B Q2_K 12.9 GB 16.00 GB 29.5 GB +3.9 GB ~1.7 llama.cpp Why
Qwen3 32B 32.8B Q2_K 12.8 GB 32.00 GB 45.4 GB +19.8 GB ~1.7 llama.cpp Why
DeepSeek-R1-Distill-Qwen 32B 32.8B Q2_K 12.8 GB 32.00 GB 45.4 GB +19.8 GB ~1.7 llama.cpp Why
Qwen2.5-Coder 32B 32.8B Q2_K 12.8 GB 32.00 GB 45.4 GB +19.8 GB ~1.7 llama.cpp Why
Gemma 4 31B 31.3B Q2_K 12.2 GB 20.78 GB 33.6 GB +8.0 GB ~1.8 llama.cpp Why
Granite 4.1 30B 28.9B Q2_K 11.3 GB 32.00 GB 43.9 GB +18.3 GB ~1.9 llama.cpp Why
Devstral Small 2 24B 24B Q2_K 9.4 GB 20.00 GB 30.0 GB +4.4 GB ~2.3 llama.cpp Why
Mistral Small 3.2 24B 23.6B Q2_K 9.2 GB 20.00 GB 29.8 GB +4.2 GB ~2.3 llama.cpp Why
Qwen3 14B 14.8B Q2_K 5.8 GB 20.00 GB 26.4 GB +0.8 GB ~3.7 llama.cpp Why
DeepSeek-R1-Distill-Qwen 14B 14.8B Q2_K 5.8 GB 24.00 GB 30.4 GB +4.8 GB ~3.7 llama.cpp Why
Qwen2.5-Coder 14B 14.8B Q2_K 5.8 GB 24.00 GB 30.4 GB +4.8 GB ~3.7 llama.cpp Why
Ministral 3 14B 13.9B Q2_K 5.4 GB 20.00 GB 26.0 GB +0.4 GB ~3.9 llama.cpp Why

Totals = quantised weights + f16 KV cache at 128K tokens + 0.6 GB runtime overhead, against 25.6 GB usable system RAM. Tokens per second are estimated from 51 GB/s peak memory bandwidth at batch 1 — not measured. Read the method.